3rd International Conference on Bioprocess and Biosystems Engineering September 14, 2015, Baltimore
Fermentation Technology, Bioprocess and
cell culture
•
•
•
•
Phototrophic vs. Dark Fermentation
Aerobic – Anaerobic – Microaerobic
online-Spectroscopy Monitoring and Control
Computational Modeling (Stoichiometric,
Kinetic, Process Models)
• Continuous Cultivation (Cytostat)
Photosynthetic Metabolism as a Source for Chemical
Products
Algae and Cyanobacteria
Biofuels
- Biodiesel
- Biohydrogen
- Bioethanol
- Lipids
etc
Photo taken from http://biology.ucsd.edu/
Purple Bacteria (Rhodospirillaceae)
-facultative photosynthetic, anoxygenic
- Single cell protein
- Vitamins
- Coenzyme Q10
- Biopesticides
- Biopolyesters
- Biofertilizers
etc.
Photosynthetic Products of Purple Non-Sulfur Bacteria
Species
Product/Application
Feedstock
Rc. gelatinosus
Wheat bran
SCP, animal feed
Rb. sphaeroides
Whey
Rb. capsulatus
Cassava starch
Cholesterol-lowering food
supplement
R. tenue
Soybean waste
R. rubrum
Biogas plant slurry
Vitamin B12
Rps. palustris
Wastewater
Carotenoids
R. molichianum
Porphyrines
Rps. viridis
Waste sulfite liquor
from wood
...
...
Enzymes
Vitamin B2
Vitamin E
Coenzyme Q10
Waste treatment
Biopolymers
Biopesticides (5-ALA)
Biohydrogen
recombinant membrane
proteins
...
Phototrophic Cultivation Systems...
Greenovation
Biotech
GmbH,
FlatpaneAirlift Reactor,
IGB Stuttgart
http://www.bio-pro.de/de/region/freiburg/magazin/04647/index.html
SCIENCE VOL 329 13 AUGUST 2010
Induction of Photosynthetic Membranes by Environmental Factors,
Oxygen and Light
+ O2: aerobic respration
- O2: anaerobic respiration, fermentation
Photosynthesis,
Formation of Intracytoplasmic membranes
- O2
+ O2
Photosynthetic gene expression repressed
Expression of photosynthetic genes
137
pfla'ack pta cbiD 411 481 L H I J K cupBcdpA C D E F
C X Y
Z WBAL M
Expression of Photosynthetic Membranes in
Purple Bacteria
• Intracytoplasmic photosynthetic
membranes in Rhodospirillum rubrum
• Cyclic photophosphorylation in
photosynthetic membranes
High Level Expression of Photosynthetic Membranes
as Model System for Redox Signaling and Control
Succinate
Succinate
Semiaerobic cultivation of R. rubrum in the dark with
different carbon substrates
High Level Expression of Photosynthetic Membranes
as Model System for Redox Signaling and Control
O2
LIGHT
CARBON
SOURCE
Fructose
Succinate
?
Fructose/Succinate
Semiaerobic cultivation of R. rubrum in the dark with
different carbon substrates
?
Redox signalling
?
Photosynthetic
gene expression
137
pfla' ack pta
cbiD
411 481
L H I J
K cupBcdpA C D E F
cdpA C D E F
C X
C X
Y
Z WBAL M
Fructose
Ghosh et al. 1994. Appl. Env. Microbiol. 60(5):1698
Grammel, H. and R. Ghosh . 2008, J. Bacteriol. 190 (14):4912-4921
Succinate
Fructose/ Succinate
Development of Rhodospirillum rubrum for Applications in
Biotechnology
- A Systems Biology Approach
Theoretical Analysis
Computational Modeling
Experimental Analysis
Bioreactor Cultivations
Kinetic modeling of electron transfer
chains and redox signaling
Metabolomics
13C isotope metabolic flux
analysis
Metabolic network analysis
Enzyme activities
Drivingforce: redoxpotential difference
E  E0, pH7 
Process modeling,
model-based control
NAD/ NADH
E0, pH 7
E
RT
[ NADH][Q]
ln
2F [NAD][QH2]
/ QH2
 320mV; E0Q, pH
90mV
7  
Thermodynamic span: ts
ts  G 2F(E 4  pmf )
Flux rNADH-DH through NADH-DH:
Gene expression profiling
rNADH-DH= kNADH-DH [NADH-DH] ts
Cybernetics models
In vivo online spectroscopy
Stoichiometric Modeling and Metabolic Network Analysis
Software Tool: CellNetAnalyzer
- stoichiometric model of central
metabolic pathways in purple
non-sulfur bacteria.
- 119 metabolites
- 142 enzymatic reactions
- MFA and FBA and FVA analysis
with measured extracellular rates
Linear metabolite balancing
equation:
dc
 0  Nr
dt
N : stoichiometric matrix
(rows: metabolites; columns: reactions with
stoichmiometric coefficients)
r: vector of reaction rates, (mmol/g h)
(Hädicke, O., H. Grammel, and S. Klamt. 2011. Metabolic
network modeling of redox balancing and biohydrogen
production in purple nonsulfur bacteria. BMC Syst. Biol.
5:150. )
www.mpi-magdeburg.mpg.de/projects/cna/cna.html
Stoichiometric Modeling and Metabolic Network Analysis
Software Tool:
CellNetAnalyzer
• MATLAB toolbox with
graphical user interface
• comprehensive toolbox
with algorithms for biological
network analysis:
- metabolic networks
- signal transduction and
regulatory networks
• Application for optimization of the
metabolic network (target reactions
for gene overexpression of knockouts)
(Hädicke, O., H. Grammel, and S. Klamt. 2011.
Metabolic network modeling of redox balancing
and biohydrogen production in purple nonsulfur
bacteria. BMC Syst. Biol. 5:150. )
www.mpi-magdeburg.mpg.de/projects/cna/cna.html
Klamt et al., 2007, BMC Systems Biology 1:2
BioMicroWorld2011
Biotechnological Potential of Purple Non-Sulfur Bacteria
Production of:
 Porphyrins
 Photodynamic Tumor Therapy
 Poly-b-hydroxyalkanoates
 Biopolymers
 Biohydrogen
 Energy carrier
 Carotenoids
 Food supplement
 Vitamins,
Coenzymes
 Food industry
 B12, Q10
 Membrane proteins
 Vaccines
…
…independent of light at microaerobic
conditions and at high cell densities !
Fructose
Succinate
Fructose/Succinate
Development of Rhodospirillum rubrum for Applications in
Biotechnology
• Photodynamic tumor therapy using bacteriochlorophyll derivatives
Laser light
1O
2
Bacteriochlorophyll a
Background image from http://www.photofrin.com
- Bacteriopheophorbide
m/z 611.2 [M+H+]+,
lmax (nm) 358, 524, 748
Biotechnological Applications of Photosynthetic Bacteria
 Biohydrogen
4,0
3000
H2
3,5
(Hädicke, O., H. Grammel, and S. Klamt. 2011. Metabolic network
modeling of redox balancing and biohydrogen production in purple
nonsulfur bacteria. BMC Syst. Biol. 5:150. )
2500
cell growth
2,5
2000
2,0
1500
1,5
1000
1,0
500
0,5
0,0
0
0
10
20
30
40
t [h]
50
60
70
80
H2 [ppm]
Cell growth [A660]
3,0
Development of Rhodospirillum rubrum , for High-Level
Expression of Industrially Relevant Carotenoids
Center Systems Biology, University of Stuttgart,
MaCS, Magdeburg Centre For Systems Biology,
crtZ
crtWmediated
Microaerobic Microbial Phenomena
Microaerobic conditions were shown to be important not only
for…
• Photosynthetic Products in R. rubrum without light
(Rudolf et al., Zeiger and Grammel, 2010; Grammel and Ghosh, Grammel et al.,)
but also for….
• bacterial pathogenicity
(Park et al., 2011; Schueller and Phillips, 2010)
• industrial waste water treatment
(Zheng and Cui, 2012)
• industrial production of cellulosic ethanol
(Agbogbo and Coward-Kelly, 2008)
• …and many others
How much Oxygen is Microaerobic?
• Microaerobic expression of
photosynthetic membranes is induced
below 0.5 % DO
• Respiratory growth in E. coli was
shown to occur at ≤ 3 nM (Stolper et
al., 2010. PNAS, 107:18755) )
•…well below the
measurement range of
conventional oxygen
probes!
Fructose
Succinate
Fructose/Succinate
Microaerobic Process Control
How to achieve microaerobic conditions in a bioreactor?
• pH-stat  photosynthetic products in R. rubrum
• Respiratory quotient  2,3 butanediol in Enterobacter
aerogenes (Zeng et al., 1994)
• Culture redox potential (CRP) as controlled variable
– many industrial and environmental processes
Expression of Photosynthetic Membranes in Bioreactor Cultivations
of Rhodospirillum rubrum under Microaerobic Dark Conditions
Grammel, H., Gilles, E.D., and Ghosh, R. (2003)
Appl Env Microbiol 69, 6577-6586
photosynthetic membrane
photosynthetic membrane
cell growth
fructose
H+
Fructose
consumption
pH decrease
-
+
air supply
-
pO2 increase
succinate
OH-
Succinate
consumption
in vivo Whole Cell UV/Vis/NIR Absorption Spectroscopy
of R. rubrum
Photosynthetic membrane expression as cellular redox indicator
AU
LH1, RC
LH1
carotenoids,
cytochrome c
LH1, RC RC
Fructose
300 400 500 600 700 800 900
nm
Succinate
Fructose/Succinate
Online Spectroscopical Process
Monitoring – Technical Equipment
Fluorescence spectrometer
Bioreactor
CCD spectrometers
Fibre optics
Model-based Control of Microaerobic Steady-States
• model-based. CRP-dependent 2DOF controller
• model-based. CRP-dependent 2DOF controller
online Biomass
and PM
spectroscopic
data
Unstructured process model
rb(CRP,xs, xf) (specific growth rate)
Dilution rate
Model
trajectory
output
trajectory
CRP – 50 mV
CRP – 100 mV
Model-based Control of
Microaerobic Steady-States
model-based 2 DOF control and
online spectroscopy allows switch
from – 50 mV to -100 mV without
disturance or oscillations.
New dilution rate adjusted to reach
the desired steady state
Biotechnological Potential of Purple Non-Sulfur Bacteria
Production of:
 Porphyrins
 Photodynamic Tumor Therapy
 Poly-b-hydroxyalkanoates
 Biopolymers
 Biohydrogen
 Energy carrier
 Carotenoids
 Food supplement
 Vitamins,
Coenzymes
 Food industry
 B12, Q10
 Membrane proteins
 Vaccines
…
…independent of light; at high cell densities ?
Fructose
Succinate
Fructose/Succinate
High Cell Density Cultivation of Rhodospirillum rubrum
Model-based high cell density cultivation:
μ
 V(t )X(t F ) μset(t  t 0 )
M S(t)  ρS  set  mS  F
e
 YX/S
 CS,Feed
~ 60 g/l cell dry weight
(Zeiger and Grammel, 2010. Biotechnol. Bioeng.105(4):729-39.)
A660 nm
Fructose
Ammonium
Succinate, Phosphate
Acknowledgements
Partners
• Biberach University of Applied Science
• Max Planck Institute for Dynamics of
Complex Technical Systems, Magdeburg
• University Stuttgart
• Center for Systems Biology, Stuttgart
• FZ Jülich
• NMI Reutlingen
• Philipps-University Marburg, Loewe
Center for Synthetic Microbiology
Process Model for R. rubrum
dt
dC Fru
dt
dC PO 4
dC NH 4
dt
Fru
FC
 q
FC
Fru
 q
dt
m
  q Cx  m Cx 
Suc
Suc
PO 4
 q
m
Cx  m Fru Cx 
V
V
( C Feed , Suc  C Suc ) 
(C Feed , Fru  C Fru ) 
FN , P
C Suc
V
FN , P
V
4.0
60
3.0
40
2.0
20
1.0
0
0.0
10 20 30 40 50 60 70 80 90 100
t (h)
C Fru
0
Cx 
FN ,P
Cx 
FN , P ´
F
F
( C Feed , NH 4  C NH 4 )  C (C Feed , NH 4 exp  C NH 4 )  C C NH 4
V
V
V
NH 4
max, sim , Fru
V
(C Feed , PO 4  C PO 4 ) 
FC
V
C PO 4
C Fru
( K Fru  C Fru )
Mixed-substrate (M2SF)
Fructose, Succinate (mM)
dC Suc
Cx
C
m m
Mixed-substrate
kineticsSuc for fed-batch
cultivation
Suc
max, sim , Suc
C2
with succinate/fructose
( K Suc  C Suc  Suc )
K i , Suc
45
4.5
40
4.0
35
3.5
30
3.0
25
2.5
20
2.0
15
1.5
10
1.0
5
0.5
0
0
mm
( k1 m Suc  k 2 m Fru )(
max, M 2 SF
C NH
C PO
1
)(
)(
)


k1 k 2 0 . 00001 C NH 0 .00001  C PO
4
10
20
30
t (h)
4
4
4
Zeiger and Grammel, 2010. Biotechnol.
Bioeng.105(4):729-39.
40
50
0.0
60
CDW (g/l)
(F
dCx  m
Cx  N , P
dt
V
Single substrates
80
CDW (g/l)
F )
C
Fructose, Succinate (mM)
Mass and volume balances
Fed-Batch Cultivation of R. rubrum: Basic Growth Parameters
Fructose
Succinate
m
C
 m
Suc
Suc
max, sim , Suc
(K
m
Suc
 C

Suc
Fru
K
C
 m
max, sim , Fru
(K
Fru
2
C
Suc
)
i , Suc
Fru
C
Fru
)
Parameter
Description
µmax, Suc
µmax, Fru
µmax, M2SF
YX/S,Suc
YX/S,Fru
YX/S,M2SF
qSuc
qFru
qSuc,M2SF
qFru,M2SF
qNH4
qPO4
maximum specific growth rate, succinate
maximum specific growth rate, fructose
maximum specific growth rate, M2SF
biomass/succinate yield coefficient
biomass/fructose yield coefficient
biomass/substrate yield coefficient, M2SF
succinate uptake rate
fructose uptake rate
succinate, mixed substrate uptake rate
fructose, mixed substrate uptake rate
ammonium uptake rate
phosphate uptake rate
µmax,sim,Suc
µmax,sim,Fru
µmax,sim,mix
YX/S,mix,Suc
YX/S,mix,Fru
YX/S,mix *
mSuc
mFru
mS
KSuc
KFru
Ki, Suc
k1
k2
k3
k4
theoretical maximum specific growth rate, succinate
theoretical maximum specific growth rate, fructose
theoretical maximum specific growth rate, mixed-substrate
biomass/succinate yield coefficient
biomass/fructose yield coefficient
biomass/substrate yield coefficient, mixed-substrate
maintenance coefficient, succinate
maintenance coefficient, fructose
maintenance coefficient, mixed-substrate
Monod saturation constant, succinate
Monod saturation constant, fructose
Monod inhibition constant, succinate
kinetic constant (Eq. [10])
kinetic constant (Eq. [10])
kinetic constant
kinetic constant
Value
0.124 (1/h)
0.123 (1/h)
0.128 (1/h)
56.32  1.06 (g/mol)
100.54  5.54 (g/mol)
68.0 (g/mol)
2.20  0.02 (mmol/g  h)
1.22  0.02 (mmol/g  h)
1.02 (mmol/g  h)
0.42 (mmol/g  h)
0.63  0.1 (mM/ g  h)
0.0125  0.003 (mM/ g  h)
0.22 (1/h)
0.12 (1/h)
1.6 (1/h)
39a /19b (g/mol)
31a /69b (g/mol)
68a / 87b (g/mol)
8.3 (µmol/g h)
16.3 (µmol/g h)
25.0 (µmol/g h)
8.7 (mM)
7.0 (mM)
42.0 (mM)
0.46
1.85
9
15
*, calculated after d´Anjou and Daugulis corresponding to the used succinate to fructose ratio.
a
batch phase, succinate/fructose ratio as in M2SF medium; bfed-batch, 0.85 M succinate to 1.66
M fructose.
Zeiger and Grammel, 2010. Biotechnol. Bioeng.105(4):729-39.
High Level Expression of Photosynthetic Membranes
as Model System for Redox Signaling and Control
O2
LIGHT
CARBON
SOURCE
Fructose
Succinate
?
Fructose/Succinate
Semiaerobic cultivation of R. rubrum in the dark with
different carbon substrates
?
Redox signalling
?
Photosynthetic
gene expression
137
pfla' ack pta
cbiD
411 481
L H I J
K cupBcdpA C D E F
cdpA C D E F
C X
C X
Y
Z WBAL M
Fructose
Ubiquinone (Coenzyme Q10);
A metabolic signal in gene regulation ?
Ghosh et al. 1994. Appl. Env. Microbiol. 60(5):1698
Grammel, H. and R. Ghosh . 2008, J. Bacteriol. 190 (14):4912-4921
Succinate
Fructose/ Succinate
Modeling the Electron Transport Chain (ETC) of Rhodospirillaceae
Issues:
anaerobic in light
-Stoichiometric model
(photosynthesis)
(elementary modes, etc.)
- Kinetic model (rate laws of
electron transfer reactions based
on redox potentials
-QH2 (Ubiquinone-10) as major
regulatory signal
Klamt, S., H. Grammel, R. Straube, R.
Ghosh, and E.D. Gilles. 2008.
Mol. Syst. Biol. 4:156.
aerobic
(respiration)
respiration + photosynthesis
Kinetic Model of the Electron Transport Chain
Kinetic description of the electron transfer processes in the ETC
based on the driving forces: redox potential differences
Driving force: redox potential difference
 DH
ENADH  DH  E0NADH

, pH 7
E
RT
[ NADH ][Q]
 ln
2F
[ NAD][QH 2]
/ NADH
/ QH 2
E0NAD
 320mV ; E0Q, pH
, pH 7
7  90mV
Thermodynamic span: ts
tsNADH-DH = – ΔG= F(2ΔENADH-DH – 4 pmf)
Reaction rate rNADH-DH :
rNADH-DH= kNADH-DH tsNADH-DH
Klamt, S., H. Grammel, R. Straube, R. Ghosh, and E.D. Gilles. 2008. Mol. Syst. Biol. 4:156.
Kinetic Model of the Electron Transport Chain
Simulation studies: Steady-state response curves of selected model variables under different environmental conditions
In vivo Spectroscopy of Cellular Redox Dynamics
NAD(P)H-fluorescence during aerobicanaerobic switch
FMN, FAD
NAD(P)H
Protein
2D fluorescence scan of bioreactor
cultivation of R. rubrum